Correlation of the Sub-micrometer Ash Yield from Pulverized Coal

Subscriber access provided by Kaohsiung Medical University

Combustion

Correlation of submicron ash yield from pulverized coal combustion with coal ash composition Lyuxiao Jiang, and Changdong Sheng Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.8b02098 • Publication Date (Web): 07 Aug 2018 Downloaded from http://pubs.acs.org on August 8, 2018

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 25 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

Correlation of submicron ash yield from pulverized coal combustion with coal ash composition Lyuxiao Jiang, Changdong Sheng School of Energy and Environment, Southeast University, Nanjing 210096, P.R. China Abstract The present work investigated the correlations of PM1 (particulate matter with the aerodynamic diameter of 4%) almost all from the well-known high alkali coals including Australian Victorian brown coal, US North Dakota lignite, and Chinese Zhundong coal. For higher rank coals (bituminous coal and anthracite claimed in the literature), in contrast, the percentage varies in a much narrower range of 0.14–2.33% with an average of 0.98% and a standard deviation of ±0.54%. Such observations demonstrate the high coal rank-dependence of the PM1 yield. The overlapping of the PM1 yields between the higher and lower rank coals in Figure 1 explains the insignificant effect of coal rank reported

ACS Paragon Plus Environment

Energy & Fuels

PM1 yield,% of the total ash mass

in some works38 where only a limited number of coals were tested. 14

Lower rank coals Higher rank coals

(a) 12 10 8 6 4 2 0 0

10

20

30

40

50

60

70


V daf, % 14

(b)

12 10 8 6 4 2 0 0

10

20

30

40

50

Ad , % PM1 yield,% of the total ash mass

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 6 of 25

14

(c)

12 10 8 6 4 2 0 0

1

2

3

4

5

6

Sd, %

Figure 1. PM1 yield is correlated with coal analytical contents, (a) Vdaf, volatile content on a dry ash free basis, (b) Ad, ash content on a dry basis, and (c) Sd, sulfur content on a dry basis.

Correlation analysis results in Table 1 show that, for all the coals, PM1 yield has a weak positive correlation with Vdaf, reflecting a weak trend of the PM1 yield increasing with volatile matter content (Figure 1a). Because Vdaf is an often used rank index, such a correlation also indicates the rank-dependence of submicron ash formation. Nevertheless, the correlation coefficients in Table 1 indicate no correlation existing between the PM1 yield and Vdaf for lower rank coals but a moderate positive correlation for higher rank coals. Table 1. Correlation coefficients between PM1 yield and coal analytical contents

a

Index

All the coals

Higher rank coals

Lower rank coals

Vdafa

0.368

0.431

-0.042

Adb

-0.362

-0.419

-0.571

Sdc

-0.073

0.199

-0.272

b

Vdaf, volatile content on a dry ash free basis; Ad, ash content on a dry basis; and Sd, sulfur content on a dry basis.

c


Page 7 of 25 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

Figure 1b displays a weak negative correlation of the PM1 yield with Ad for all the coals. As considered separately, moderate negative correlations are present for both lower and higher rank coals but with the lower rank coals having a relatively stronger correlation (Table 1). These negative correlations suggest that, for a coal with lower ash content, a larger fraction of its ash is likely to transform into submicron ash particles, as also observed by Zellagui et al.39 in experimental study and explained by the difference in ash chemical composition. As for sulfur content, Figure 1c and Table 1 indicate no correlation existing with the PM1 amount for all the coals, and only a weak positive and a weak negative correlation appearing for the higher and lower rank coals, respectively. The weak positive correlation for higher rank coals is consistent with the rough trend detected for bituminous coals by Buhre et al.32 3.2 Correlations between PM1 yield and ash composition Figure 2 presents PM1 yield correlating with the contents of major ash-forming elements. The corresponding correlation coefficients listed in Table 2 indicate that, for all the coals, PM1 yield has a strong, moderate and weak negative correlation with SiO2, Al2O3 and TiO2, respectively; strong positive correlations with Na2O and MgO, a moderate positive correlation with CaO, an extremely weak positive correlation with Fe2O3, but a weak negative correlation with K2O. These reflect the general trends of PM1 yield decreasing with the contents of acidic constituents, i.e., SiO2, Al2O3 and TiO2, and increasing with the contents of basic constituents, Na2O, MgO and CaO, of coal ash (Figure 2). To consider the coal rank-dependence, correlation analyses were conducted for the higher and lower rank coals, separately. The obtained correlation coefficients are also listed in Table 2. As can be seen, for higher rank coals, there are almost no correlations of PM1 yield with the contents of individual ash constituents except for a weak negative correlation with SiO2 and a weak positive correlation with Fe2O3. For lower rank coals, in contrast, there are stronger negative correlations with SiO2, Al2O3, TiO2 and K2O and somewhat weaker correlations with Na2O, CaO and MgO than those for all the coals. A moderate positive correlation also exhibits with Fe2O3 for lower rank coals with the correlation coefficient comparable to those of other basic oxides.



14

Lower rank coals Higher rank coals

(a)

12 10 8 6 4 2 0 0

10

20

30

40

50

60

70

80

Page 8 of 25

14

(b)

12 10 8 6 4 2 0

90

0

10

20

14

(c)

12 10 8 6 4 2 0 0

0.5

1

1.5

2

2.5

3

3.5

(d)

10 8 6 4 2 0 0

1

2

3



10 8 6 4

(e) 2 0

5

6

15

20

14

7

(f)

12 10 8 6 4 2 0

25

0

10

20

30

40

50

CaO, % PM1 yield,% of the total ash mass

Na2O, % 14

4

K2O, %

12

10

50

12

4

14

5

40

14

TiO2, %

0

30

Al2O3, % PM1 yield,% of the total ash mass


SiO2, %


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Energy & Fuels

14

(g)

12

(h)

12

10

10

8 6 4 2 0 0

5

10

15

20

8 6 4 2 0 0

10

MgO, %

20

30

40

50

Fe2 O3, %

Figure 2. PM1 yield is correlated with elemental oxide contents of coal ash, (a) SiO2, (b) Al2O3, (c) TiO2, (d) K2O, (e) Na2O, (f) CaO, (g) MgO, and (h) Fe2O3.

Considering multiple elements contributing to PM1 formation, PM1 yield is then related to the simple sums of some acidic or basic oxide contents. The resulting correlation coefficients are summarized in Table 3. The correlations with SiO2+Al2O3 and Na2O+MgO are illustrated in Figures 3a and 3b as examples. Generally, great improvements are achieved by the summed contents of acidic oxides over the individual oxides for both all the coals and lower rank coals, as indicated by much higher correlation coefficients in Table 3 compared to the relevant ones in Table 2. The summed content of all acidic oxides (A=SiO2+Al2O3+TiO2)


Page 9 of 25 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

has the highest correlation coefficients, marginally higher than those of SiO2+Al2O3. In contrast, no improvements are observed for the summed contents of basic oxides of all the coals and slight improvements for some sums of lower rank coals. The exception is Na2O+MgO, which has the correlation coefficients of 0.88 and 0.85 for all the coals and lower rank coals, respectively, much higher than individual Na2O or MgO and other sums of basic oxides. These extremely strong correlations reflect the significant contributions of Na and Mg to submicron ash formation especially from lower rank coals.44,79

Table 2. Correlation coefficients between PM1 yield and ash composition Index

All the coals

Higher rank coals

Lower rank coals

SiO2

-0.625

-0.214

-0.735

Al2O3

-0.527

-0.128

-0.550

TiO2

-0.210

-0.112

-0.289

K2 O

-0.247

0.006

-0.354

Na2O

0.783

-0.162

0.700

CaO

0.591

0.152

0.484

MgO

0.789

0.153

0.730

Fe2O3

0.182

0.225

0.563

Attempt was also made to correlate PM1 yield with the contents of all the major oxides by multiple linear regression. The obtained correlations are: For all the coals, PM1 = - 0.003 SiO2 - 0.002 Al2O3 + 0.049 K2O + 0.350 Na2O + 0.036 CaO + 0.309 MgO + 0.018 Fe2O3, R2 = 0.878; (1) For lower rank coals, PM1 = - 0.007 SiO2 - 0.050 Al2O3 + 0.084 K2O + 0.285 Na2O + 0.069 CaO + 0.252 MgO + 0.103 Fe2O3, R2 = 0.916. (2) The determination coefficients R2, equivalent to r2, indicate much better correlations than those with individual and simply summed oxide contents for all the coals and the lower rank coals and even for the higher rank coals. The negative values of the regressed coefficients for SiO2 and Al2O3 and positive values of the regressed coefficients for basic oxides in the equations implies the PM1 yield decreasing with the acidic oxides contents and increasing with the basic oxide contents, which are consistent with the results of the correlation analyses for individual oxide contents except K2O.


Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 10 of 25

Table 3. Correlation coefficients of PM1 yield with summed oxide contents of coal ash Index

All the coals

Higher rank coals

Lower rank coals

SiO2+Al2O3

-0.705

-0.201

-0.813

Aa

-0.718

-0.240

-0.817

a

A +K2O

-0.715

-0.244

-0.798

Na2O+MgO

0.881

0.083

0.850

Na2O+CaO

0.718

0.142

0.647

MgO+ Fe2O3

0.445

0.245

0.715

Na2O+ K2O

0.508

-0.071

0.341

CaO+MgO

0.697

0.169

0.621

Na2O+MgO+CaO

0.780

0.158

0.732

Na2O+MgO+Fe2O3

0.642

0.231

0.758

CaO+MgO+Fe2O3

0.628

0.245

0.720

Na2O+MgO+CaO+Fe2O3

0.714

0.242

0.798

0.718

0.240

0.817

b

B a

A denotes the summed contents of all acid oxides, i.e., SiO2, Al2O3 and TiO2; bB represents the

summed contents of all basic oxides.

The discernible trends in Figure 2 show PM1 yield increasing with the contents of basic oxides except K2O and decreasing with the contents of acidic oxides. Therefore, the ratios of the content or summed content of basic oxides to the summed content of acidic oxides are further correlated with PM1 yield. The obtained correlation coefficients as well as the regressed correlations for all the coals and lower rank coals are compiled in Table 4. As expected, systematic improvement is achieved over the sums of both the basic and acidic oxides. The correlation coefficients indicate that most of the ratios have extremely strong correlations with PM1 yield for both all the coals and the lower rank coals. The best correlation for all the coals exists with (Na2O+MgO)/(SiO2+Al2O3) or (Na2O+MgO)/A ratio and the best for the lower rank coals with (Na2O+MgO+Fe2O3)/A and (Na2O+MgO)/A, which are shown in Figures 3c and 3d as examples. It is noteworthy that, Na2O/(SiO2+Al2O3) ratio is an often used to reflect the contribution of Na to PM1 formation,14,64 it is shown here, however, to have a relatively lower degree of correlation with PM1 yield (Figure 3e). Fair good linear correlations are also observed with base/acid (B/A) ratio (B denotes the summed content of all basic oxides) for lower rank coals, as presented in Figure 3f. As can be seen, the correlation with B/A ratio is obviously skewed by one coal sample. With it excluded, the correlation coefficient increases significantly from 0.87 to 0.94, implying the strong contributions of basic elements to submicron ash formation particularly from burning lower rank coals.


PM1 yield % of the total ash mass

14

Lower rank coals Higher rank coals Lower rank coals All the coals

(a)

12 10 8 6 4 2 0 10

20

30

40

50

60

70

80

90

14

(b) 12 10 8 6 4 2 0

100

0

5

10

15

14

(c)

12 10 8 6 4 2 0 0

0.2

0.4

0.6

0.8

1

8 6 4 2 0 0.3

40

10 8 6 4 2 0 0


10

0.2

35

0.5

0.4

0.5

1

1.5

2

(Na2 O+MgO+Fe2 O3)/A, %

(e)

0.1

30

(d)

12

1.2

14

0

25

14

(Na2O+MgO)/(SiO2+Al2O3), %

12

20

Na2O+MgO, % PM1 yield,% of the total ash mass


SiO2 +Al2O3 , %


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels


Page 11 of 25

0.6

14

(f)

12 10 8 6 4 2 0

0.7

0

0.5

1

Na2O/(SiO2 +Al2O3), %

1.5

2

2.5

3

B/A

Figure 3. PM1 yield is correlated with the combined indexes (ratios) of ash composition, (a) SiO2+Al2O3, (b) Na2O+MgO, (c) (Na2O+MgO)/(SiO2+Al2O3), (d) Na2O/(SiO2+Al2O3), (e) (Na2O+MgO+ Fe2O3)/A, and (f) B/A. The solid and dash lines show the regressed trend for lower rank coals and all the coals, respectively. Table 4. Correlations of PM1 yield with the ratios of oxide contents of coal ash All the coals Index

Equation

(Na2O+MgO)/( SiO2+Al2O3)

a

Higher rank coals

Lower rank coals

r

r

Equationa

r

y = 12.414x+0.8096

0.908

0.117

y = 11.588x+1.3279

0.885

(Na2O+MgO)/A

y = 12.232x+0.8202

0.909

0.117

y = 11.397x+1.3307

0.887

Na2O/( SiO2+Al2O3)

y = 18.953x+1.1994

0.822

-0.017

y = 16.336x+2.1663

0.773

b

MgO/( SiO2+Al2O3)

y = 21.642x+0.8777

0.839

-0.008

y = 19.405x+1.7456

0.805

(Na2O+MgO+CaO)/( SiO2+Al2O3)

y = 4.6434x+0.5213

0.818

0.020

y = 4.4778x+1.1381

0.791

(Na2O+MgO+CaO)/Ab

y = 4.7595x+0.5146

0.824

0.020

y = 4.5931x+1.1159

0.798

(Na2O+MgO+Fe2O3)/A c

B /A

b

a

b

y = 5.5074x+0.4754

0.748

0.168

y = 6.7794x+0.8247

0.888

y = 4.5293x-0.2411

0.788

0.169

y = 5.0239x-0.3317

0.872

The equations were derived by the linear regression analysis with x and y representing the index

and PM1 yield, respectively. bA denotes the summed contents of all acid oxides, i.e., SiO2, Al2O3 and c

TiO2. B represents the summed contents of all basic oxides.


Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

4. Discussion 4.1 Rank-dependence of PM1 yield and its correlation with coal and ash composition The correlation analysis reveals evident rank-dependence of PM1 yield and its correlation with coal and ash composition. Such dependence observed is on two aspects. One is the positive correlation existing between PM1 yield and Vdaf particularly for higher rank coals (Figure 1a). It may be attributed to two reasons. Firstly, in addition to the vaporization of refractory oxides/metals during char combustion,24 the release of organically bounded metals associated with coal devolatilization may also play a substantial role in PM1 formation.45,59-61,78 As volatile matter content of the coal increases, therefore, more organically bound metals are likely to release during devolatilization to contribute in PM1 formation.39,59 Additionally, a coal with a higher rank index value generally produces the char with a higher reactivity during pulverized coal combustion.81 The resulting char may burn at a relatively higher temperature, favoring the vaporization of refractory oxides/metals to form more submicron ash. However, the moderate correlation implies that PM1 formation is unlikely to be dominated by ranking itself and related coal burning behavior. The composition and distribution of inorganic matter in coal are the determinants of submicron ash formation.44,45 It is well known that inorganic matter in higher rank coals occurs mostly as discrete minerals and most of minerals are refractory. In contrast, much more inorganic matter in lower rank coals occurs as organically bound and ion-exchangeable species as well as salts, which are highly potential to vaporize during combustion.24,41,44 It explains burning lower rank coals generally generates much more PM1 than burning higher rank coals (Figure 1). Moreover, all the organically bound elements, mainly Na, Ca, Mg as well as Fe in lower rank coals,41 may be released during pulverized coal combustion to participate into submicron ash formation. It determines the very much higher correlations between PM1 yield and the contents of all the oxides for lower rank coals than those for higher rank coals. Therefore, the second aspect of the rank-dependence of PM1 yield and its correlation with coal and ash composition is ascribed to the rank-dependent occurrence of the inorganic matter in coals.


Page 12 of 25

Page 13 of 25 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

4.2 Dependence of PM1 yield on ash composition As shown in Figure 2, positive correlations exist between PM1 yield and the contents of basic oxides except K2O. It is expected because Na-containing species in coal62,64 are largely vaporizable and refractory oxides, MgO and CaO,24 and Fe-containing species44,65 can be chemically reduced to vaporize during char burnout to make their contributions to the formation of PM1 and particularly fine mode particles. The degrees of their correlations with PM1 yield are in line with the vaporization potentials of the elements during pulverized coal combustion.44,45 According to the measurements of Quann et al.,44 the averages of 41% Na and 20% Mg in lower rank coals and 25% Na and 2.2% Mg in higher rank coals vaporize and end in submicron fume; the average of 2.2% Fe in most of coals vaporizes but it can be much higher up to 40% for some coals; and the vaporization of Ca is much less with the averages of about 1% and 0.1% for lower and higher rank coals, respectively. The strongest correlations of Na2O and MgO with the PM1 yield for all the coals and for lower rank coals (Table 2) reflect the significance of their vaporization to PM1 formation due to their high volatility despite their relatively lower contents in coal ash. Indeed, Na and Mg are often observed major elements in submicron ash especially from burning lower rank coals.15,24,44,45 Although a considerable fraction of Fe vaporizes to form submicron particles,44,45 nearly no correlation with Fe2O3 for all the coals but a moderate positive correlation for lower rank coals (Table 2) are ascribed mainly to the dependence of the vaporization on Fe occurrence in coal, which is highly variable and coal type-dependent.44 As for Ca, it is generally similar to Mg in chemical properties and modes of occurrence in coal.44 Nevertheless, its fractional vaporization is one order of magnitude lower than that of Mg during the combustion of both lower and higher rank coals.44 As a result, the concentration of CaO in submicron ash was observed to be much lower than that of MgO particularly for lower rank coals,15,24,44 although the content of CaO in coal ash are generally much higher than that of MgO. The higher content of CaO in coal ash but very lower potential of Ca vaporization may explain PM1 yield correlating worse with CaO and its combinations than with MgO and its combinations (Tables 2 and 3). Because the vaporized fractions of Na, Mg and Ca are significantly rank-dependent,44 the rank-dependence of the correlations with the contents of their oxides are expected, representing the distinct differences in the occurrences of these elements between lower and


Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

higher rank coals. The strong negative correlation between PM1 yield and SiO2 content is a bit surprising. Although the vaporization fraction of Si is very low,44,45 as the average determined to be 1.25% by Quann et al.,44 SiO2 is always a major constituent of submicron ash especially from burning higher rank coals due to its high content in coal ash. The reason for the negative correlation may be that Si occurs with quartz, silicates and aluminosilicates in coal. Under high temperatures of pulverized coal combustion, they may melt and react with Na-,33,62-64 Mg-,33,73,74 Ca-,33,73 and Fe-containing species33,65 to hamper the release of these basic constituents to form PM1, dominating over Si vaporization. The mineral occurrence also explains the negative correlation of PM1 yield with Al2O3 because Al occurs in coal mostly as aluminosilicates, potential to participate in the melting and reactions during combustion, while it is among the least vaporizable major elements and generally makes little contribution to PM1 formation.19,44 It even explains the negative correlation of K2O with the PM1 yield. Alkali element K is often observed to enrich it submicron ash particles, relative to the content of K2O in coal ash.63 However, K in coals mostly occurs in non-volatile aluminosilicates and vaporizes merely through the replacement reactions of Na-bearing vapors.63 The higher content of K2O in coal ash implies relatively more K is likely to end in residual ash along with aluminosilicate transformations rather than vaporize, which therefore enhances the interactions to retain or capture other volatile species. Given that sufficient Na is present in the coal and released into gas phase during combustion, the contribution of K to PM1 formation through the replacement reactions is likely to increase with K2O content. Such a trend is roughly observable in Figure 1d for the high alkali lower rank coals (coals with PM1 yield higher than 4% of the total ash mass). But it is not the case for other lower and higher rank coals. The effects of the mineral association and related interaction behavior of ash constituents on submicron ash formation may also explain great improvements achieved by the summed acidic oxide contents over the individual acidic oxide contents while no improvements by the summed basic oxide contents over the individuals except for Na2O+MgO. This difference may be attributed to the highly associated behavior of SiO2 and Al2O3 during ash transformations and the relatively independent behavior of basic components in the


Page 14 of 25

Page 15 of 25 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

vaporization and contribution to PM1 formation. The higher summed content of SiO2 and Al2O3 may imply their higher association as aluminosilicate minerals in coal, which not only depresses the vaporization of SiO2 as well as Al2O3 and the fragmentation of ash particles but also enhances the retention or capture of basic elements such as Na62. In contrast, the relatively independent behavior of basic components vaporizing means fewer PM1 formation-related interactions between them, resulting in no improvements on the correlations. Additionally, it is interesting to find in Tables 3 and 4 that the sum and ratio indexes with Fe2O3 included have much weaker correlations with PM1 yield for all the coals than those for lower rank coals while the indexes without Fe2O3 present reverse trends. It may imply that, while Fe2O3 itself vaporizes to become a major component of submicron ash from all the coals,44 it also plays a depressing role in ash vaporization through participating in and enhancing melting-related interactions of the minerals during ash formation of particularly lower rank coals. Among the summed contents of basic oxides, Na2O+MgO has the strongest correlations with PM1 yield for both all the coals and the lower rank coals (see Table 3). B content and Na2O+MgO+CaO+Fe2O3 have the second and third strongest correlation for lower rank coals. As for the ratio indexes examined, all present extremely strong or very strong positive correlations with PM1 yield. Most of the ratios have higher correlation coefficients (Table 4) than the summed contents for both all the coals and the lower rank coals (Table 3). These further suggest that basic ash constituents except K2O make the major contributions to PM1 formation particularly from lower rank coals;24 the higher contents of acidic oxides in coal ash may reduce submicron ash formation although the vaporization of SiO2 also contributes greatly to submicron ash quantity. It also justifies the rationality of using aluminosilicates, such as kaolinite, and Anatase (TiO2) as additives to reduce PM1 emission from pulverized coal combustion through their capturing the alkais.64,70,82- 86 Correlation coefficients in Tables 1-4 indicate that, for higher rank coals, there are no correlations or very weak correlations between PM1 yield and all ash-related indexes as well as coal sulfur content. On the other hand, higher rank coals exhibit a moderate positive correlation between PM1 yield and Vdaf, which actually has the highest correlation coefficient among all the indexes evaluated for higher rank coals, while lower rank coals have no such a


Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

correlation. As the volatile matter content is not only an index of coal rank but also an indicator of coal combustion characteristics. It may imply that PM1 formation from burning higher rank coals is likely to depend on coal combustion characteristics in addition to ash composition and chemistry. For lower rank coals, in contrast, the correlations of ash-related indexes are all very much stronger. It suggests submicron ash formation from lower rank coals is dominated by ash composition and chemistry. 4.3 The uncertainties related to PM1 yield and its correlation with ash composition It should be noticed that, although the PM1 yields surveyed were from burning pulverized coals under similar experimental conditions, there are variations in the combustion temperature and residence time, coal particle size, and PM1 determination methods (see supporting information). These variations may affect the amount of submicron ash formed or the value reported and, together with the variations in determining coal properties, lead to the scattering of the data (Figure 3) and consequently the uncertainties for the correlations derived. The upper size limit used to define submicron ash (or PM1) in literature works differs from 0.4 µm for sole fine mode particles to the cascade impactor size-cut close to 1 µm (see supporting information). Such a difference certainly affects the PM1 yield reported. Actually, the boundary between the fine and central mode varies with coal properties and combustion conditions and is uneasy to ascertain because of the nature of the two modes overlapping. The boundary size determined also relies on the definitions used to distinguish the two modes.18,19,27 For example, from burning 15 coals in air in a DTF at 1673 K, Teramae and Takayuki27 detected the upper boundary of the fine mode at 0.33 µm from particle mass-size distributions and at 0.22 µm from elemental mass-size distributions. Fine mode particles formed through vaporization-condensation mechanism commonly centers at 0.1–0.2 µm but the upper limit of the mode can reach much larger sizes because of the formation of aggregates with the sizes of 0.3–0.6 µm.66 On the other hand, the presence of residue fly ash can extend to 0.2–0.5 µm, as indicated by the elemental size distributions and enrichment factor data of refractory elements in fine ash particles.8 Therefore, the appropriate size limit for the fine mode was often suggested to be as low as 0.5 µm.16,18,67 Using a boundary line of


Page 16 of 25

Page 17 of 25 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

above this size thus inevitably includes some central mode particles in the PM1, also implying that using different boundary sizes may cause the uncertainty in the PM1 yields reported. Even so, the mass of the fine mode particles is dominant, accounting for 70 – 90% of the total mass of the PM1.87 Moreover, the formation of the central mode particles has complex mechanisms. Among them, the fine fragmentation of residual ash16,17 and subsequent heterogeneous condensation of vaporized species such as alkali- and sulfur-bearing vapors on the fine fragments18,26,27 are widely recognized to be important. Studies on the elemental mass-size distributions8,18,27 revealed that the contribution of the heterogeneous condensation of the vapors on other particles up to the size of 0.76 – 2.5 µm is considerable and increases greatly with the particle size decreasing. The main reason is that the vapors preferentially condense on ash particles of >0.3 µm while their condensation on finer fume particles is relatively depressed due to the Kelvin effect despite the high surface area of the fume.62 As a result, the heterogeneous condensation makes significant contribution to the mass of particularly the finer fraction of the central mode particles. In other words, a considerable mass of the finer central mode particles also originates from vaporization-condensation. It partially explained the fairly good relationships observed between PM1 yield and the contents of vaporizable ash constituents such as Na2O (Figure 2e). The measurements of PM1 yield were performed at various furnace or gas temperatures of 1400–1773 K but mostly in the range of 1500–1750 K. As stated in the Introduction, the temperature is a determining factor affecting PM1 formation. Therefore, the temperature variation is believed to be also one of the main factors leading to the data scattering. According to the estimation of Helble and Sarofim,50 however, such a difference in gas temperature has only a slight effect on the temperatures of char particles burning in air, i.e., 100 K or less, because the char particles burn under an extreme diffusion-controlled regime at these temperatures. Moreover, the impact of the burning temperature on the vaporization and submicron ash formation is on two aspects: a higher temperature enhances the vaporization of refractory species; a higher temperature also promotes ash fusion and interactions, thus enhances the retention of volatile species such as alkali species in residual ash and capture of the vapors in gas phase.62 Given that the char particles burning under the extreme diffusion-controlled regime, the effect of the resulting burning temperature difference on PM1


Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

formation may not be very significant although a higher gas temperature, to some extent, certainly increases PM1 formation as widely observed.33,35 It explains the good correlations showed in Figure 3 despite the range of the temperatures involved. Particle sizes of the coal samples used in the experiments are various, pulverized coal or different narrowly sized particles, which affects PM1 formation. Nevertheless, the extent of its influence is less than other factors such as the temperature.35 As for the residence time, its variation is not believed to considerably influence the PM1 yields measured39,68 because the ashes were all sampled far after the full conversion of pulverized coal. Difference in the methods for determining ash composition may also cause the uncertainty in the correlations with PM1 yield. In the literature works, ash composition was determined by directly measuring elemental contents in the coal or quantifying the composition of laboratory ash produced by ashing the coal at low or high temperature. The biggest difference may be that high temperature ashing causes the loss of a fraction of ash constituents, mainly Na-containing species, through vaporization, leading to relatively lower content of Na2O than directly measuring coal elements or analyzing low temperature ash. It is thus expected to have larger impact on ash composition of lower rank coals due to their higher contents of volatile constituents. Nevertheless, the high correlation coefficients of Na2O related indexes suggest the influence of this uncertainty on the correlations may be insignificant. 4.4 Applicability of the correlations to estimate PM1 yield from pulverized coal combustion In spite of the above uncertainties, some fairly good correlations derived imply the significant dependence of the PM1 yield from pulverized coal combustion on ash composition. The correlations are therefore potentially applicable to estimate submicron ash yield from pulverized coal combustion based on ash composition. Taking the correlation of (Na2O+MgO)/(SiO2+Al2O3) ratio and Eq 1 for all the coals and the correlation of B/A ratio and Eq 2 for lower rank coals as examples, the PM1 amount estimated by using the linear correlations are compared with the measurements in Figure 4. The results show that the estimations are plausible with more than 60% of the predictions within ±30% of the


Page 18 of 25

Page 19 of 25

measurements, implying the applicability of the correlations is promising for practical purpose. For example, the correlations can be used as guidance for selecting coals for PM1 emission reduction. 14

14

(a) (Na2O+MgO)/(SiO2+Al2O3) ratio for all the coals

(b) Equation 1 for all the coals 12 10

10

Estimated PM1 yield

Estimated PM1 yield

12

8 6 4

8 6 4 2

2

0

0 0

2

4

6

8

10

12

14

0

2

4

Measured PM1 yield

6 8 10 Measured PM1 yield

12

14

12

14

14

14

(c) B/A ratio for lower rank coals

(d) Equation 2 for lower rank coals

12

12

10

10

Estimated PM1 yield

Estimated PM1 yield

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

8 6 4

8 6 4 2

2

0

0 0

2

4

6

8

10

12

14

0

2

Masured PM1 yield

4

6 8 10 Measured PM1 yield

Figure 4. Estimated PM1 yields with the linear correlation of (a) (Na2O+MgO)/(SiO2+Al2O3) ratio and (b) Eq 1 for all the coals and the linear correlation of (c) B/A ratio and (d) Eq 2 for lower rank coals are compared with the measurements. The close and open symbols represent the data for lower and higher rank coals, respectively. The solid lines indicate the estimation equaling to the measured value, while the dashed lines denote ±30% deviation.

It should be noted that the PM1 yields used for the correlation analysis were mostly from burning pulverized coal in DTFs. Even though the gas temperature and coal particle size and heating rate as well as the resulting particle burning temperatures resemble those in industrial furnaces, the high bulk oxygen concentration and diluted combustion condition are quite different from the reality, which may result in less vaporization of refractory elements such as Ca80 and therefore less PM1. Nevertheless, it is noteworthy that six sets of data included in the analyses were taken from the experiments in a pilot-scale combustor that simulates pulverized coal combustion processes in real furnaces.30,43 Moreover, some field measured PM1 data and related ash composition6 were also examined and found to be well fitted with all good correlations (not shown here). It means that the good correlations established here are potentially applicable for estimating the PM1 yield from normal pulverized coal combustion


Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

in industrial furnaces. However, as stated in the Introduction, PM1 formation depends on combustion conditions. For example, low NOX combustion such as air staging, which is common for modern industrial furnaces, increases PM1 formation from lower rank coals.30,43 Oxygen-enriched combustion promotes PM1 formation through enhancing refractory oxides/elements vaporization.31,32,37 Oxyfuel combustion at the same oxygen concentration generally lowers PM1 formation as compared to air firing.36-38 Fortunately, the effects of these conditions on PM1 formation can be well described by modeling.54-56 5. Conclusion PM1 yields, together with analytical data of coal and ash composition, from burning pulverized coals under similar conditions in laboratory reactors were collected from open literature. A large database containing 75 coals was thus formed to enable examining and establishing the correlations between PM1 yield and the coal and particularly ash composition amidst the experiments related variations and uncertainties. The following main conclusions were drawn from the investigation: 1) PM1 yield from pulverized coal combustion highly varies among coals and particularly among lower rank coals. The correlation analysis reveals, more or less, the linear correlations existing between PM1 yield and the coal analytical contents (volatile matter, ash and sulfur contents) and ash composition indexes including the contents of individual oxides and the sums and ratios of oxide contents. The correlations and their degrees are strongly rank-dependent. Such dependence of the correlations between PM1 yield and ash composition indexes is mainly ascribed to the rank-dependence of the inorganic matter occurrence in coal. For higher rank coals, the rank-dependence of coal combustion characteristics may play a role as well. 2) For all the coals and lower rank coals, PM1 yield has positive correlations with the contents of basic oxides of coal ash except K2O and th degrees of correlation are in line with the vaporization potentials of these basic constituents. PM1 yield has a strong, moderate, and weak negative correlation with SiO2, Al2O3, and K2O, respectively. These negative correlations are attributed to their associated minerals preferentially participating in ash melting and reactions during combustion to retain or capture volatile species,


Page 20 of 25

Page 21 of 25 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

mostly basic constituents, and thus decreasing PM1 formation. 3) The correlations of PM1 yield with the summed acidic oxide contents were observed to be generally stronger than those with the individual acidic oxide contents of coal ash, while the correlations with the summed basic oxide contents except for Na2O+MgO are weaker than those with the individuals. The difference may be attributed respectively to the highly associated behavior of SiO2 and Al2O3 during ash transformation and the relatively independent behavior of basic components in the vaporization and contribution to PM1 formation. 4) PM1 yield has pretty good correlations with the ratios of the content or summed content of basic oxides to the summed content of acidic oxides of coal ash, with most of ratios evaluated displaying extremely strong correlation for all the coals and lower rank coals. 5) Fairly good correlations exist between PM1 yield and some combined indexes of ash composition, including Na2O+MgO, (Na2O+MgO)/(SiO2+Al2O3) ratio, B/A ratio, and the linear combination. These correlations are potentially applicable for estimation of PM1 formation from pulverized coal combustion of all the coals and lower rank coals for practical purpose. Acknowledgement The authors acknowledge partial supports from the National Key Research and Development Program of China (2016YFB0600601), International Science & Technology Cooperation Program of China (2015DFA60410), and National Science Foundation of China/National Science Foundation (USA) joint grant (51661125011). References (1) Flagan, R. C.; Friedlander, S. K. Particle Formation in Pulverized Coal Combustion-A Review. In Recent Developments in Aerosol Science (D. T. Shaw, ed.). 25-59, Wiley: New York, 1978. (2) Markowski, G. R.; Ensor, D. S.; Hooper, R. G.; Carr, R. C. Environ. Sci. Technol. 1980, 14, 1400-1402. (3) Taylor, D. D.; Flagan, R. C. Aerosol Sci. Technol. 1982, 1, 103-117.


Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

(4) McElroy, M. W.; Carr, R. C.; Ensor, D. S.; Markowski, G. R. Science 1982, 215, 13-19. (5) Lighty, J. S.; Veranth, J. M.; Sarofim, A. F. J. Air Waste Manage. 2000, 50 (9), 1565-1618. (6) Nielsen, M. T.; Livbjerg, H.; Fogh, C. L.; Jensen, J. N.; Simonsen, P.; Lund, C.; Poulsen, K.; Sander, B. Combust. Sci. Technol. 2002, 174 (2), 79-113. (7) Xu, M.; Yu, D.; Yao, H.; Liu, X.; Qiao, Y. Proc. Combust. Inst. 2011, 33, 1681-1697. (8) Markowski, G. R.; Fiiby, R. Environ. Sci. Technol. 1985, 19, 796-805. (9) Kaupplnen, E. I.; Pakkanen, T. A. Environ. Sci. Technol. 1990, 24, 1811 –1818. (10) Ylätalo, S. I.; Hautanen, J. Aerosol Sci. Technol. 1998, 29, 17-30. (11) Helble, J.J. Fuel Process. Technol. 2000, 63, 125-147. (12) Zhan, Z.; Fry, A.; Zhang, Y.; Wendt, J. O. L. Proc. Combust. Inst. 2015, 35, 2373–2380. (13) Zhan, Z.; Fry, A. R.; Wendt, J. O. L. Fuel 2016, 181, 1214-1223. (14) Zhan, Z.; Wendt, J. O. L. Energy Fuels 2017, 31, 2198−2202. (15) Neville, M.; Quann, R. J.; Haynes, B. S.; Sarofim, A. F. Symp. (Int.) Combust., [Proc.] 1981, 18 (1), 1267-1274. (16) Linak, W. P.; Miller, C. A.; Seames, W. S.; Wendt, J. O. L.; Ishinomori, T.; Endo, Y.; Miyamae, S. Proc. Combust. Inst. 2002, 29, 441–447. (17) Seames, W. S. Fuel Process. Technol. 2003, 81, 109– 125. (18) Yu, D.; Xu, M.; Yao, H.; Sui, J.; Liu, X.; Yu, Y.; Cao, Q. Proc. Combust. Inst. 2007, 31, 1921–1928. (19) Yu, D.; Xu, M.; Yao, H.; Liu, X.; Zhou, K. Powder Technol. 2008, 183, 105–114. (20) Seames, W. S.; Fernandez, A.; Wendt, J. O. L. Environ. Sci. Technol. 2002, 36, 2772-2776. (21) Carbone, F.; Beretta, F.; D’Anna, A. Energy Fuels 2010, 24, 6248–6256. (22) Flagan, R. C. Symp. (Int.) Combust., [Proc.] 1979, 17 (1), 97-104. (23) Flagan, R. C.; Taylor, D. D. Symp. (Int.) Combust., [Proc.] 1981, 18 (1), 1227-1237. (24) Quann, R. J.; Sarofim, A. F. Symp. (Int.) Combust., [Proc.] 1982, 19 (1), 1429-1440. (25) Sarofim, A. F.; Howard, J. B.; Padia, A. S. Combust. Sci. Technol. 1977, 16 (3-6), 187-204. (26) Yu, D.; Xu, M.; Yao, H.; Liu, X.; Zhou, K.; Li, L.; Wen, C. Proc. Combust. Inst. 2009, 32,


Page 22 of 25

Page 23 of 25 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

2075–2082. (27) Teramae, T.; Takarada, T. Energy Fuels 2009, 23, 2018–2024. (28) Fix, G.; Seames, W. S.; Mann, M. D.; Benson, S. A.; Miller, D. J. Fuel Process. Technol. 2011, 92, 793–800. (29) Fix, G.; Seames, W.; Mann, M.; Benson, S.; Miller, D. Fuel 2013, 113, 140–147. (30) Linak, W. P.; Peterson, T. W. Aerosol Sci. Technol. 1984, 3 (1), 77-96. (31) Buhre, B. J. P.; Hinkley, J. T.; Gupta, R. P.; Wall, T. F.; Nelson, P. F. Fuel 2005, 84, 1206–1214. (32) Buhre, B. J. P.; Hinkley, J. T.; Gupta, R. P.; Nelson, P. F.; Wall, T. F. Fuel 2006, 85, 185–193. (33) Zhang, L.; Ninomiya, Y.; Yamashita, T. Fuel 2006, 85, 1446–1457. (34) Ninomiya, Y.; Zhang, L.; Sato, A.; Dong, Z. Fuel Process. Technol. 2004, 85, 1065– 1088. (35) Liu, X.; Xu, M.; Yao, H.; Yu, D.; Gao, X.; Cao, Q.; Cai, Y. Energy Fuels 2007, 21, 157-162. (36) Sheng, C.; Li, Y.; Liu, X.; Yao, H.; Xu, M. Fuel Process. Technol. 2007, 88, 1021-1028. (37) Jia, Y.; Lighty, J. S. Environ. Sci. Technol. 2012, 46, 5214−5221. (38) Kazanc, F.; Levendis, Y. A. Energy Fuels 2012, 26, 7127−7139. (39) Zellagui, S.; Trouvé, G.; Schönnenbeck, C.; Zouaoui-Mahzoul, N.; Brilhac, J. F. Fuel 2017, 189, 358–368. (40) Gao, X.; Li, Y.; Garcia-Perez, M.; Wu, H. Energy Fuels 2012, 26, 6783−6791. (41) Gao, X.; Rahim, M. U.; Chen, X.; Wu, H. Fuel 2014, 117, 825-832. (42) Zhang, P.; Yu, D.; Luo, G.; Yao, H. Energy Fuels 2015, 29, 5245−5252. (43) Linak, W. P.; Peterson, T. W. Symp. (Int.) Combust., [Proc.] 1986, 21 (1), 399-410. (44) Quann, R.J.; Neville, M.; Sarofim, A.F. Combust. Sci. Technol. 1990, 74, 245-265. (45) Zhang, L.; Ninomiya, Y. Fuel 2006, 85, 194–203. (46) Wang, Q.; Zhang, L.; Sato, A.; Ninomiya, Y.; Yamashita, T. Energy Fuels 2007, 21, 756-765. (47) Zhang, L.; Wang, Q.; Sato, A.; Ninomiya, Y.; Yamashita, T. Energy Fuels 2007, 21, 766-777.


Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

(48) Wen, C.; Gao, X.; Yu, Y.; Wu, J.; Xu, M.; Wu, H. Fuel 2015, 140, 526–530. (49) Ruscio, A.; Kazanc, F.; Levendis, Y. A. J. Energy Eng. 2016, 142, E4015007. (50) Helble, J. J.; Sarofim, A. F. Combust. Flame 1989, 76, 183-196. (51) Baxter, L. L. Combust. Flame 1992, 90, 174-184. (52) Senior, C.L.; Flagan, R. C. Aerosol Sci. Technol. 1982, 1, 371-383. (53) Niu, Y.; Wang, S.; Shaddix, C. R.; Hui, S. Combust. Flame 2016, 173, 195–207. (54) Chen, Y.; Jiang, L.; Zhang, H.; Sheng, C. Energy Fuels 2018, 32, 4323-4333. (55) Lee, C. M.; Davis, K. A.; Heap, M. P.; Eddings, E.; Sarofim, A. Proc. Combust. Inst. 2000, 28 (2), 2375–2382. (56) Eddings, E. G.; Sarofim, A. F.; Lee, C. M.; Davis, K. A.; Valentine, J. R. Fuel Process. Technol. 2001, 71, 39–51. (57) Sui, J.; Xu, M.; Qiu, J.; Qiao, Y.; Yu, Y.; Liu, X.; Gao, X. Energy Fuels 2005, 19, 1536-1541. (58) Gao, Q.; Li, S.; Yuan, Y.; Zhao, Y.; Yao, Q. Energy Fuels 2016, 30, 1815−1821. (59) Zhang, L.; Ninomiya, Y.; Yamashita, T. Energy Fuels 2006, 20, 1482-1489. (60) Gao, X.; Wu, H. Energy Fuels 2011, 25, 4172–4181. (61) Wen, C.; Fan, B.; Wang, W.; Zeng, X.; Yu, G.; Lv, W.; Xu, M. Energy Fuels 2017, 31, 224−230. (62) Neville, M.; Sarofim, A. F. Fuel 1985, 64, 384-390. (63) Gallagher, N. B.; Bool, L. E.; Wendt, J. O. L.; Peterson, T. W. Combust. Sci. Technol. 1990, 74 (1-6), 211-221. (64) Gallagher, N. B.; Peterson, T. W.; Wendt, J. O. L. Symp. (Int.) Combust., [Proc.] 1996, 26 (2), 3197–3204. (65) Zeng, T.; Helble, J. J.; Bool, L. E.; Sarofim, A. F. Fuel 2009, 88, 566–572. (66) Helble, J.; Neville, M.; Sarofim, A.F. Symp. (Int.) Combust., [Proc.] 1988, 21 (1), 411–417. (67) Moisio, M.; Laitinen, A.; Hautanen, J.; Keskinen, J. J. Aerosol Sci. 1998, 29 (Suppl 1), S459-S460. (68) Zhuo, J. K.; Li, S. Q.; Yao, Q.; Song, Q. Proc. Combust. Inst. 2009, 32, 2059–2066. (69) Quann, R. J. Ash Vaporization under Simulated Pulverized Coal Combustion Conditions.


Page 24 of 25

Page 25 of 25 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

PhD Thesis, Massachusetts Institute of Technology: Department of Chemical Engineering, 1977. (70) Zhou, K.; Xu, M.; Yu, D.; Liu, X.; Wen, C.; Zhan, Z.; Yao, H. Energy Fuels 2010, 24, 6266–6274. (71) Ruan, R.; Tan, H.; Wang, X.; Li, Y.; Li, S.; Hu, Z.; Wei, B.; Yang, T. Fuel 2018, 211, 206–213. (72) Xiao, Z.; Shang, T.; Zhuo, J.; Yao, Q. Fuel 2016, 181, 1257-1264. (73) Ninomiya, Y.; Wang, Q.; Xu, S.; Mizuno, K.; Awaya, I. Energy Fuels 2009, 23, 3412–3417. (74) Ninomiya, Y.; Wang, Q.; Xu, S.; Teramae, T.; Awaya, I. Energy Fuels 2010, 24, 199–204. (75) Wei, Y.; Wang, Q.; Zhang, L.; Awaya, I.; Ji, M.; Li, H.; Yamada, N.; Sato, A.; Ninomiya, Y. Fuel Process. Technol. 2013, 105, 188-194. (76) Zhang, L.; Ninomiya, Y.; Wang, Q.; Yamashita, T. Fuel 2011, 90, 77-86. (77) Wang, C.; Liu, X.; Li, D.; Wu, W.; Xu, Y.; Si, J.; Zhao, B.; Xu, M. Int. J. Greenh. Gas Con. 2014, 23, 51-60. (78) Wen, C.; Yu, D.; Wang, J.; Wu, J.; Yao, H.; Xu, M. Energy Fuels 2014, 28, 5682−5689. (79) Neville, M.; Sarofim, A. F. Symp. (Int.) Combust., [Proc.] 1982, 19 (1), 1441-1449. (80) Wu, H.; Pedersen, A. J.; Glarborg, P.; Frandsen, F. J.; Dam-Johansen, K.; Sander, B. Proc. Combust. Inst. 2011, 33, 2845-2852. (81) Sun, J. K.; Hurt, R. H. Proc. Combust. Inst. 2000, 28, 2205–2213. (82) Mwabe, P. O.; Wendt, J. O. L. Symp. (Int.) Combust., [Proc.] 1996, 26, 2447-2453. (83) Takuwa, T.; Naruse, I. Fuel Process. Technol. 2007, 88, 1029–1034. (84) Takuwa, T.; Naruse, I. Proc. Combust. Inst. 2007, 31, 2863–2870. (85) Chen, J.; Yao, H.; Zhang, P.; Xiao, L.; Luo, G.; Xu, M. Proc. Combust. Inst. 2011, 33, 2837–2843. (86) Xu, Y.; Liu, X.; Zhang, Y.; Sun, W.; Hu, Y.; Xu, M. Fuel 2017, 193, 72–80. (87) Li, C.; Wen, C.; Wang, W.; Wang, W.; Chen, H.; Yu, D.; Xu, M. Proc. Combust. Inst. 2018, https://doi.org/10.1016/j.proci.2018.07.012.


Correlation of the Sub-micrometer Ash Yield from Pulverized Coal

Recommend Documents